Rail (real) safety issues: predictive maintenance for Singapore railway

This Final Year Project (FYP) aims to evaluate the possibility of performing fault prediction in Singapore’s rail network from available data. The quest to predict railway faults in Singapore is still underway, spearheaded by the Rail Enterprise Asset Management System (REAMS) project jointly led by...

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Main Author: Khoo, Alyna Yi Jie
Other Authors: Ling Keck Voon
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157583
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1575832023-07-07T19:31:08Z Rail (real) safety issues: predictive maintenance for Singapore railway Khoo, Alyna Yi Jie Ling Keck Voon School of Electrical and Electronic Engineering EKVLING@ntu.edu.sg Engineering::Electrical and electronic engineering This Final Year Project (FYP) aims to evaluate the possibility of performing fault prediction in Singapore’s rail network from available data. The quest to predict railway faults in Singapore is still underway, spearheaded by the Rail Enterprise Asset Management System (REAMS) project jointly led by SIEMENS and ST Engineering Consortium formed in 2018. This project’s main purpose is to identify useful indicators in existing data that can be used as performance indicators for predictive maintenance. The focus is on the observable trends in the Automatic Train Supervision (ATS) and Corrective Maintenance Data (CMD) records, with findings supported by the F&D Daily Report, Workorder (WO), and Fault & Delay (F&D) data. This report covers the analytic approaches taken and their results to evaluate the possibility of performing predictive maintenance in Singapore’s rail network. It also briefly covers existing shortcomings of the available datasets. As no predictive maintenance has been implemented in Singapore’s rail network, the commencement and submission of this project is done in the hope that the identified shortcomings may be overcome, and featured potential performance indicators can be built upon to establish a foundation for predictive maintenance in Singapore’s rail network. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-21T05:18:22Z 2022-05-21T05:18:22Z 2022 Final Year Project (FYP) Khoo, A. Y. J. (2022). Rail (real) safety issues: predictive maintenance for Singapore railway. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157583 https://hdl.handle.net/10356/157583 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Khoo, Alyna Yi Jie
Rail (real) safety issues: predictive maintenance for Singapore railway
description This Final Year Project (FYP) aims to evaluate the possibility of performing fault prediction in Singapore’s rail network from available data. The quest to predict railway faults in Singapore is still underway, spearheaded by the Rail Enterprise Asset Management System (REAMS) project jointly led by SIEMENS and ST Engineering Consortium formed in 2018. This project’s main purpose is to identify useful indicators in existing data that can be used as performance indicators for predictive maintenance. The focus is on the observable trends in the Automatic Train Supervision (ATS) and Corrective Maintenance Data (CMD) records, with findings supported by the F&D Daily Report, Workorder (WO), and Fault & Delay (F&D) data. This report covers the analytic approaches taken and their results to evaluate the possibility of performing predictive maintenance in Singapore’s rail network. It also briefly covers existing shortcomings of the available datasets. As no predictive maintenance has been implemented in Singapore’s rail network, the commencement and submission of this project is done in the hope that the identified shortcomings may be overcome, and featured potential performance indicators can be built upon to establish a foundation for predictive maintenance in Singapore’s rail network.
author2 Ling Keck Voon
author_facet Ling Keck Voon
Khoo, Alyna Yi Jie
format Final Year Project
author Khoo, Alyna Yi Jie
author_sort Khoo, Alyna Yi Jie
title Rail (real) safety issues: predictive maintenance for Singapore railway
title_short Rail (real) safety issues: predictive maintenance for Singapore railway
title_full Rail (real) safety issues: predictive maintenance for Singapore railway
title_fullStr Rail (real) safety issues: predictive maintenance for Singapore railway
title_full_unstemmed Rail (real) safety issues: predictive maintenance for Singapore railway
title_sort rail (real) safety issues: predictive maintenance for singapore railway
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157583
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